4 key learnings attendees will take away from this webinar:
- The value of good design of experiments
- Consider Bayesian statistics to answer your question
- P-values is not always what you’re looking for
- Adopt a life-cycle over the long-run, not just study by study.
For 15 years the scientific literature has repeatedly underlined the important lack of reproducibility and replicability of studies in biomedical research. As a consequence, several scientific organisations (journal, scientific societies, universities, national agencies) have identified some root causes to this issue and proposed good research practices to improve the replicability of the results. The misuse of statistical concepts, from design of studies to analysis of data to decision-making is at the heart of the crisis, even if not the only cause. In this webinar we will explain the how to understand the sequences of issues and how to fix it in order to drastically improve the replicability of the results. Through example the presentation will cover concepts such as OFAT vs DoE, p-values and Bayesian statistics and Power vs Assurance as easy opportunities to improve robustness of decisions.